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Computational intelligence for decision support

Author: Zhengxin Chen
Publisher: Boca Raton, Fla. : CRC Press, ©2000.
Series: CRC Press international series on computational intelligence.
Edition/Format:   eBook : Document : EnglishView all editions and formats

Intelligent decision support relies on techniques from a variety of disciplines, including artificial intelligence and database management systems. This book offers an explanation of how to use AI  Read more...


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Genre/Form: Fulltext
Internet Resources
Additional Physical Format: Print version:
Chen, Zhengxin.
Computational intelligence for decision support.
Boca Raton, Fla. : CRC Press, ©2000
(DLC) 99049863
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Zhengxin Chen
ISBN: 9781420049145 1420049143
OCLC Number: 47160495
Description: 1 online resource (xv, 380 pages) : illustrations.
Contents: DECISION SUPPORT AND COMPUTATIONAL INTELLIGENCE The Need for Decision Support Agents Computerized Decision Support Mechanisms Computational Intelligence for Decision Support A Remark on Terminology Data, Information, and Knowledge Issues to be Discussed in This Book SEARCH AND REPRESENTATION Sample Problems and Applications of Computational Intelligence Definition of Computational Intelligence Basic Assumptions of Computational Intelligence Basic Storage and Search Structures Problem Solving Using Search Representing Knowledge for Search State Space Search Remark on Constraint-Based Search Planning and Machine Learning as Search PREDICATE LOGIC First Order Predicate Logic Prolog for Computational Intelligence Abduction and Induction Nonmonotonic Reasoning RELATIONS AS PREDICATES The Concept of Relation Overview of Relational Data Model Relational Algebra Relational Views and Integrity Constraints Functional Dependencies Basics of Relational Database Design Multivalued Dependencies Remark on Object-Oriented Logical Data Modeling Basics of Deductive Databases Knowledge Representation Meets Databases RETRIEVAL SYSTEMS Database Management Systems (DBMS) Commercial Languages for Database Management Systems Basics of Physical Database Design An Overview of Query Processing and Transaction Processing. Information Retrieval (IR) Data Warehousing Rule-Based Expert Systems Knowledge Management and Ontologies CONCEPTUAL DATA AND KNOWLEDGE MODELING OVERVIEW Entity-Relationship Modeling Remark on Legacy Data Models Knowledge Modeling for Knowledge Representation Structured Knowledge Representation Frame Systems Conceptual Graphs User Modeling and Flexible Inference Control REASONING AS EXTENDED RETRIEVAL Beyond Exact Retrieval Reasoning as Query-Invoked Memory Re-Organization COMPUTATIONAL CREATIVITY AND COMPUTER ASSISTED HUMAN INTELLIGENCE Computational Aspects of Creativity Idea Processors Retrospective Analysis for Scientific Discovery and Technical Invention Combining Creativity with Expertise CONCEPTUAL QUERIES AND INTENSIONAL ANSWERING A Review of Question Answering Systems Intensional Answering and Conceptual Query An Approach for Intensional Conceptual Query Answering FROM MACHINE LEARNING TO DATA MINING Basics of Machine Learning Inductive Learning Efficiency and Effectiveness of Inductive Learning Other Machine Learning Approaches Features of Data Mining Categorizing Data Mining Techniques Association Rules DATA WAREHOUSING, OLAP, AND DATA MINING Data Mining in Data Warehouses Decision Support Queries, Data Warehouse, and OLAP Data Warehouse as Materialized Views and Indexing Remarks on Physical Design of Data Warehouses Semantic Differences Between Data Mining and OLAP Nonmonotonic Reasoning in Data Warehouding Environment Combining Data Mining and OLAP Conceptual Query Answering Data Warehouses Web Mining REASONING UNDER UNCERTAINTY General Remarks on Uncertain Reasoning Uncertainty Based on Probability Theory Fuzzy Set Theory Fuzzy Rules and Fuzz Expert Systems Using Fuzzy CLIPS Fuzzy Controllers The Nature of Fuzzy Logic REDUCTION AND RECONSTRUCTION APPROACHES FOR UNCERTAIN REASONING AND DATA MINING The Reduction-Reconstruction Duality Some Key Ideas of K-systems Theory and Rough Set Theory Rough Sets Approach K-Systems Theory TOWARD INTEGRATED HEURISTIC DECISION MAKING Integrated Problem Solving High-Level Heuristics for Problem Solving and Decision Support Meta-Issues for Decision Making Each section also contains an overview, summary, and self-examination questions.
Series Title: CRC Press international series on computational intelligence.
Responsibility: Zhengxin Chen.


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